Introducing locally affine-invariance constraints into lunar surface image correspondence
Zhang, Yu-Ren1; Yang, Xu1; Qiao, Hong1,3; Liu, Zhi-Yong1; Liu, Chuan-Kai2
2016-04-19
发表期刊NEUROCOMPUTING
卷号186期号:页码:258-270
文章类型Article
摘要This paper aims to solve the keypoint correspondence problem in lunar surface images, a typical correspondence task under point ambiguity. Point ambiguity may be caused by repetitive patterns, cluttered scenes, and outliers in the images, which makes the local descriptors less discriminative. In this paper we introduce locally affine-invariance constraints on graphs to tackle the keypoint correspondence problem under point ambiguity. The key idea is that each point can be represented with the affine combination of its neighbors. It is suitable for our problem because it is not only invariant to scale and rotational change, but also more resistant to outliers. Specifically, we introduce the locally affine-invariance constraints into the subgraph matching problem and the common subgraph matching problem. The locally affine-invariance constraint is not directly applicable on common subgraph matching due to its dependency on awareness of selected keypoints. This problem is approximately addressed by solving a series of reliable matching identification and rematching problems. In the experiments, we first apply the proposed method on standard graph matching datasets to evaluate its effectiveness on general correspondence problem under point ambiguity, and second validate the applicability on the lunar surface image dataset. (C) 2016 Elsevier B.V. All rights reserved.
关键词Keypoint Correspondence Point Ambiguity Graph Matching Lunar Image Processing
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2015.12.082
关键词[WOS]ROBUST ; GNCCP
收录类别SCI
语种英语
项目资助者National Science Foundation of China (NSFC)(61375005 ; Beijing Municipal Science & Technology Commission(2141100002014002) ; National Key Technology RD Program(2012BAI34B02) ; 61033011 ; 61210009 ; 61101221)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000374366300025
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11629
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
通讯作者Yang, Xu
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
2.Beijing Aerosp Flight Control Ctr, Beijing, Peoples R China
3.Chinese Acad Sci, CEBSIT, Shanghai, Peoples R China
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Zhang, Yu-Ren,Yang, Xu,Qiao, Hong,et al. Introducing locally affine-invariance constraints into lunar surface image correspondence[J]. NEUROCOMPUTING,2016,186(无):258-270.
APA Zhang, Yu-Ren,Yang, Xu,Qiao, Hong,Liu, Zhi-Yong,&Liu, Chuan-Kai.(2016).Introducing locally affine-invariance constraints into lunar surface image correspondence.NEUROCOMPUTING,186(无),258-270.
MLA Zhang, Yu-Ren,et al."Introducing locally affine-invariance constraints into lunar surface image correspondence".NEUROCOMPUTING 186.无(2016):258-270.
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